A Method and System for Parallel Testing of Power Consumption and Performance of a Communication Module

Abstract

The present invention provides a method and system for parallel testing of the power consumption and performance of a communication module, which relates to the technical field of communication module testing. The specific scheme includes: obtaining the power consumption data and communication performance data of the communication module, and forming a multi-dimensional vector matrix through discretization processing; based on the multi-dimensional vector matrix of the communication module, calculating the dynamic correlation between communication modules, and constructing a multi-dimensional dynamic correlation matrix; using the multi-dimensional dynamic correlation matrix to estimate the interaction effects between communication modules, and adjusting the resource allocation ratio between communication modules according to the interaction effects; after the resource allocation is completed, generating a final comprehensive test result according to the performance of power consumption and communication performance in actual testing; the present invention considers the mutual influence and interaction relationship between the two, conducts comprehensive testing on the communication module, and improves the efficiency and accuracy of testing.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication module testing, and particularly relates to a method and system for parallel testing of the power consumption and performance of a communication module. Background Art

[0002] With the rapid development of the Internet of Things, smart grid, and 5G communication technologies, communication modules, as key network connection devices, are widely used in various intelligent devices and terminals. Communication modules undertake important tasks such as data collection, information transmission, and device control in these scenarios. Their performance and power consumption directly affect the stability and energy efficiency of the entire system. Especially in application fields such as smart meters, smart homes, and intelligent transportation, the communication performance and power consumption of communication modules have become important indicators for evaluating the overall performance of devices.

[0003] With the increasingly complex application requirements, the testing of communication modules has gradually expanded from single-functional testing to comprehensive testing of power consumption and performance. Communication modules are usually in different working states, such as standby, data transmission, receiving instructions, etc. The power consumption performance and communication performance in different states have significant differences. Especially in low-power Internet of Things application scenarios, communication modules need to achieve lower power consumption while maintaining good communication performance. Therefore, how to accurately test the power consumption and communication performance of communication modules in different states in real time and effectively evaluate the mutual relationship between the two has become an important task in the design, research, and optimization process of communication modules.

[0004] The prior art cannot achieve parallel testing of power consumption and communication performance. It often needs to be tested separately, which cannot accurately reflect the mutual influence and interaction relationship between the two, resulting in low testing efficiency, lack of analysis ability for the complex interaction between power consumption and communication performance, inability to identify the dynamic association between modules and the impact of power consumption changes on communication performance, inflexible resource allocation, easy to cause resource waste or unreasonable allocation, and failure to maximize the use of testing resources, resulting in low testing efficiency. Summary of the Invention

[0005] To overcome the deficiencies of the above prior art, the present invention provides a method and system for parallel testing of the power consumption and performance of a communication module, which considers the mutual influence and interaction relationship between the two, conducts comprehensive testing on the communication module, and improves the efficiency and accuracy of testing.

[0006] To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:

[0007] The first aspect of the present invention provides a method for parallel testing of the power consumption and performance of a communication module.

[0008] A method for parallel testing of the power consumption and performance of a communication module includes:

[0009] Obtain the power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing;

[0010] Based on the multi-dimensional vector matrix of the communication module, calculate the dynamic correlation between communication modules and construct a multi-dimensional dynamic correlation matrix;

[0011] Estimate the interaction influence between communication modules using the multi-dimensional dynamic correlation matrix, and adjust the resource allocation ratio between communication modules according to the interaction influence;

[0012] After the resource allocation is completed, generate the final comprehensive test result according to the performance of power consumption and communication performance in actual tests.

[0013] Further, the power consumption data includes the current, voltage, and power of the communication module in different working states;

[0014] The communication performance data includes the signal strength, transmission rate, network delay, and signal anti-attenuation ability of the communication module;

[0015] The sampling of the power consumption data and communication performance data is carried out in parallel, and the same clock source is used for synchronous sampling to ensure that the power consumption data and communication performance data at each moment can be accurately corresponding to the same time point.

[0016] Further, the discretization is to eliminate the temporal continuity and data noise between different modules, construct the discrete signals of the communication module at specific time steps, and form a multi-dimensional vector matrix with the discrete signals of all time steps within the entire test period.

[0017] Further, the calculation of the dynamic correlation between communication modules is based on the multi-dimensional vector matrix of the communication module, calculate the change rate of the discrete signal over time, and combine the product of the change rates with the modulation of the cosine function to obtain the influence of the phase difference between communication modules on the dynamic correlation, and determine the degree of correlation between communication modules.

[0018] Further, the estimation of the interaction influence between communication modules using the multi-dimensional dynamic correlation matrix is to quantify the mutual influence between communication modules based on the correlation degree between standardized communication modules and the phase difference between communication modules adjusted by the time variation factor.

[0019] Further, the adjustment of the resource allocation ratio between communication modules according to the interaction influence is to use a hierarchical scheduling model to adjust the resource allocation weight according to the interaction influence and feedback results to obtain the optimal resource allocation ratio.

[0020] Further, the comprehensive test result is based on the actual power consumption of the communication module, the maximum allowable value of the power consumption, the actual communication performance, and the minimum and maximum values of the communication performance. It evaluates the performance of power consumption and communication performance in parallel, and sums the weighted power consumption performance and communication performance as the final comprehensive test result.

[0021] The second aspect of the present invention provides a parallel test system for the power consumption and performance of a communication module.

[0022] A parallel test system for the power consumption and performance of a communication module includes a data acquisition module, a correlation calculation module, an impact estimation module, and a result generation module:

[0023] The data acquisition module is configured to: acquire the power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing;

[0024] The correlation calculation module is configured to: calculate the dynamic correlation between communication modules based on the multi-dimensional vector matrix of the communication module, and construct a multi-dimensional dynamic correlation matrix;

[0025] The impact estimation module is configured to: estimate the interaction impact between communication modules using the multi-dimensional dynamic correlation matrix, and adjust the resource allocation ratio between communication modules according to the interaction impact;

[0026] The result generation module is configured to: after the resource allocation is completed, generate the final comprehensive test result according to the performance of power consumption and communication performance in the actual test.

[0027] The third aspect of the present invention provides a computer-readable storage medium, on which a program is stored. When the program is executed by a processor, it implements the steps in a parallel test method for the power consumption and performance of a communication module as described in the first aspect of the present invention.

[0028] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps in a parallel test method for the power consumption and performance of a communication module as described in the first aspect of the present invention.

[0029] The above one or more technical solutions have the following beneficial effects:

[0030] 1. Through a series of data processing steps such as discretization, correlation matrix calculation, and interaction impact estimation, the present invention can accurately analyze the complex interaction relationship between the power consumption and communication performance of each communication module; different from the traditional method that only relies on simple power consumption or performance test results, the present invention uses a multi-dimensional dynamic correlation matrix to accurately identify the interaction impact between communication modules and provides more comprehensive test data through quantitative analysis.

[0031] 2. Through the adaptive hierarchical scheduling model, the present invention realizes the intelligent allocation of test resources; in the case of limited resources, by dynamically adjusting the test tasks and resource allocation ratios of each communication module, it ensures that system resources can be reasonably allocated, maximizes the test efficiency, and reduces interference between modules; the resource allocation strategy is based on the interaction effects and historical feedback between communication modules, can dynamically adjust the test priorities, avoid resource waste, and improve the test accuracy.

[0032] 3. By the weighted combination of power consumption data and communication performance data, the present invention can comprehensively evaluate the overall performance of communication modules; it can not only test the performance of communication modules in a single aspect, but also find the best balance between power consumption and communication performance, helping developers optimize module designs and ensuring that communication modules can maintain low power consumption and high communication performance under different working conditions.

[0033] 4. The present invention introduces a feedback optimization mechanism that can adjust resource allocation according to the test results of each round. By analyzing the actual test performance of each communication module, the system can dynamically adjust the test tasks and resource allocation strategies for the next round, thereby gradually optimizing the entire test process. This adaptive feedback mechanism ensures the gradual improvement of the test process, makes the power consumption and performance test results closer to the actual application requirements, and guarantees the flexibility and intelligence of the entire test system.

[0034] Advantages of additional aspects of the present invention will be partially given in the following description, partially become obvious from the following description, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings forming a part of this specification are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation to the present invention.

[0036] Figure 1 It is a flowchart of the method for Embodiment 1. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0038] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0039] Embodiment 1

[0040] In an embodiment of the present disclosure, a method for parallel testing of the power consumption and performance of a communication module is provided. As Figure 1 shown, it includes the following steps:

[0041] Step S1: Obtain the power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing.

[0042] Furthermore, the power consumption data includes the current, voltage, and power of the communication module in different working states;

[0043] The communication performance data includes the signal strength, transmission rate, network latency, and signal anti-attenuation ability of the communication module;

[0044] The sampling of the power consumption data and the communication performance data is carried out in parallel, and the same clock source is used for synchronous sampling to ensure that the power consumption data and the communication performance data at each moment can be accurately corresponding to the same time point.

[0045] Furthermore, the discretization is to eliminate the temporal continuity and data noise between different modules, construct the discrete signals of the communication module at specific time steps, and form a multi-dimensional vector matrix with the discrete signals of all time steps within the entire test period.

[0046] Specifically, initialize the communication module to be tested, detect whether the hardware connection of the module is normal, and calibrate all input signals before sampling to ensure that the communication module to be tested operates under standard working conditions.

[0047] The main objective of data sampling is to obtain two types of key data of the communication module: power consumption data and communication performance data; in order to ensure the synchronous and accurate acquisition of these two types of data, parallel processing is carried out through independent hardware sensors and acquisition modules.

[0048] Power consumption data acquisition requires real-time monitoring of the current, voltage, and power of the communication module in different working states, especially measuring the static power consumption of the module (i.e., the power consumption when the module is in an idle or standby state) and the dynamic power consumption (i.e., the power consumption when the module is performing communication tasks).

[0049] The collection of communication performance data mainly includes the signal strength, transmission rate, network latency, signal anti-attenuation ability, etc. of the communication module. Through a series of special test equipment, such as signal analyzers, spectrum analyzers, etc., the signal parameters sent and received by the real-time communication capture module during the communication process are captured.

[0050] The collection of power consumption data and communication performance data is carried out in parallel. In order to ensure the consistency of the two types of data in terms of time sequence, a clock synchronization mechanism is introduced. All collection devices use the same clock source for synchronous sampling to ensure that the power consumption data and communication performance data at each moment can be accurately corresponding to the same time point.

[0051] Preprocess the collected power consumption data and communication performance data. Through data preprocessing, the power consumption data and communication performance data are converted into discrete signals and form a multi-dimensional vector matrix: First, discretize the data to eliminate the temporal continuity and data noise between different modules, so as to form a multi-dimensional vector suitable for processing in space, making the data structure more suitable for further correlation calculation. The discretization formula is as follows:

[0052]

[0053] Among them, represents the discrete signal of the i-th communication module at time t, which combines the power consumption data and the communication performance data ; is the power consumption measurement value at the th moment, is the number of discrete time steps, representing the time sequence number at the discrete moment; is the total number of time steps within the entire test period; is the communication performance measurement value at the th moment; The parameter is the attenuation factor of historical data, which is used to adjust the influence of historical power consumption and communication performance data on the current moment data; is the start time of the test, and the set period is the average working duration of the current communication module within the test period.

[0054] Step S2: Based on the multi-dimensional vector matrix of the communication module, calculate the dynamic correlation between communication modules and construct a multi-dimensional dynamic correlation matrix.

[0055] Furthermore, the calculation of the dynamic correlation between communication modules is based on the multi-dimensional vector matrix of the communication module, calculating the change rate of the discrete signal over time, combining the product of the change rates with the modulation of the cosine function to obtain the influence of the phase difference between communication modules on the dynamic correlation, and determining the degree of correlation between communication modules.

[0056] Specifically, by calculating the multi-dimensional dynamic correlation matrix between different communication modules, the complex interaction relationship between the power consumption and communication performance of each communication module is evaluated. By quantifying the correlation between multiple communication modules, their mutual influence is determined, especially the influence of power consumption changes on communication performance and the reaction of communication performance changes on power consumption, and the dynamic correlation between each communication module is found. The calculation formula of the correlation matrix is:

[0057]

[0058] Wherein, represents the dynamic correlation matrix between the i-th communication module and the j-th communication module at time t; by calculating the time derivatives of the discrete signals and of two communication modules, their rates of change over time are obtained; the product of the rates of change combined with the modulation of the cosine function reflects the influence of the phase difference between communication modules on the dynamic correlation.

[0059] Through the calculation of dynamic correlation, the correlation strength between different communication modules is determined, especially in the interaction between power consumption and communication performance, providing a reference basis for subsequent interaction estimation and resource scheduling.

[0060] Step S3: Estimate the interaction between communication modules using the multi-dimensional dynamic correlation matrix, and adjust the resource allocation ratio between communication modules according to the interaction.

[0061] Furthermore, the estimation of the interaction between communication modules using the multi-dimensional dynamic correlation matrix is based on the correlation degree between standardized communication modules and the phase difference between communication modules adjusted by the time variation factor to quantify the mutual influence between communication modules.

[0062] Furthermore, the adjustment of the resource allocation ratio between communication modules according to the interaction is to use a hierarchical scheduling model to adjust the resource allocation weight according to the interaction and feedback results to obtain the optimal resource allocation ratio.

[0063] Specifically, the correlation matrix is used to estimate the interaction between each communication module. By evaluating the coupling relationship between power consumption and performance, the mutual influence between communication modules is quantified, especially to identify the situations of mutual interference and modulation between communication modules during the test. The estimation formula of the interaction is:

[0064]

[0065] Wherein, represents the interaction between the i-th communication module and the j-th communication module at time t; Through the normalization operation, the correlation degree between the i-th communication module and the j-th communication module is standardized to ensure that the total interactive influence of each communication module is 1; reflects the phase difference between two communication modules , and through the time variation factor dynamically adjusts the influence coefficient; the parameter is a time-related modulation coefficient used to control the attenuation degree of the phase difference and ensure that the interactive influence is dynamically adjusted over time.

[0066] According to the estimation of the interactive influence, resources for power consumption testing and communication performance testing are dynamically allocated. The resource allocation for power consumption testing and communication performance testing is dynamically carried out through a unified resource pool. The resources in the resource pool can include:

[0067] Testing device time: such as the usage time of the power consumption testing device and the communication performance testing device.

[0068] Computing power: The processing ability for power consumption and communication performance data. Especially for high-precision tests, more computing power may be required.

[0069] Measurement accuracy and frequency: Different test units (power consumption and communication performance testing) may require different sampling frequencies or accuracies to obtain accurate measurement data.

[0070] These resources will be dynamically adjusted according to the interactive influence of the module and the correlation matrix to ensure that the test results of each module are as accurate as possible.

[0071] In this context, the resource allocation formula does not directly allocate between power consumption testing and communication performance testing, but determines the priority of the overall resources of each module. The overall resources include: resources for power consumption testing (such as the usage time of power measurement devices, measurement accuracy, etc.) and resources for communication performance testing (such as rate measurement devices, data throughput testing devices, etc.).

[0072] Therefore, the formula actually assigns the proportion of the overall resources for each module. This proportion will affect the priority of the module in power consumption testing and communication performance testing, and thus affect the resource usage between the two.

[0073] If a module has a greater interactive influence, it will obtain more resources, especially when the trade-off between power consumption and communication performance is more complex.

[0074] Resource allocation affects the accuracy and coverage of testing. Based on the priority of resource allocation, the system determines how much resource to allocate to power consumption testing and communication performance testing during each testing period. This priority is dynamically optimized by adjusting to achieve dynamic optimization.

[0075] If a higher proportion of resources is allocated to a certain module, then the power consumption testing or communication performance testing of this module will be more accurate.

[0076] Therefore, in the case of limited resources, the test tasks of each communication module are reasonably scheduled to maximize the test efficiency and minimize the interference between communication modules; to achieve this, according to the dynamic adjustment process of interaction influence, historical data, test accuracy, and resource allocation priority, an implicit hierarchical division is adopted to construct a hierarchical scheduling model, and the resource allocation weight is adjusted according to the interaction influence and feedback results. Among them, the formula for the resource allocation weight is:

[0077]

[0078]

[0079] Among them, represents the resource allocation ratio of the i-th communication module at time t, that is, the resource allocation weight; represents the interaction influence of the i-th communication module from the j-th communication module and combines it with the weight of the j-th communication module combined; represents adjustment through the time decay coefficient to ensure balanced resource allocation and avoid over-concentration of resources; is the average value of the dynamic association of all communication modules, used to measure the overall resource distribution state.

[0080] The feedback result refers to the adjustment and optimization of resource allocation after each round of testing. In the resource allocation formula, the adjustment of feedback is reflected by the following formula:

[0081]

[0082] The feedback result refers to the optimization adjustment of resource allocation by the system according to the previous round of test results (including the actual performance of power consumption and communication performance ).

[0083] ​On the premise of ensuring the balance between the power consumption and communication performance tests of each communication module, optimize resource allocation and dynamically adjust the test priorities according to the feedback results; through the output of the hierarchical scheduling formula, adjust the allocation ratio of resources in real time to provide the optimal scheduling scheme for the tests.

[0084] Step S4: After the resource allocation is completed, generate the final comprehensive test result according to the performance of power consumption and communication performance in the actual test.

[0085] In each round of testing during the resource allocation process, the test results of power consumption and communication performance are collected and calculated in real time according to the current resource allocation strategy (such as ), and test data and .

[0086] The comprehensive test result is based on the actual power consumption of the communication module, the maximum allowable value of power consumption, the actual communication performance, and the minimum and maximum values of communication performance, parallelly evaluate the performance of power consumption and communication performance, and perform a weighted sum of the power consumption performance and communication performance performance as the final comprehensive test result.

[0087] After the resource allocation is completed, generate the final comprehensive test result according to the performance of power consumption and communication performance in the actual test. The specific formula is:

[0088]

[0089] Wherein, represents the comprehensive test result of the communication module at time t, reflecting the overall performance of the communication module; is the actual power consumption of the communication module at time t (unit: watt); represents the maximum allowable value of power consumption, which is the power upper limit of the hardware design (unit: watt); is the actual communication performance of the communication module at time t, such as communication rate or data throughput (unit: bit / second); and are respectively the minimum and maximum values of communication performance; is the power consumption weight coefficient, is the communication performance weight coefficient, .

[0090] By performing a weighted sum of the power consumption performance and communication performance performance, comprehensively evaluate the performance of the communication module. A value close to 1 indicates that the communication module has low power consumption and excellent communication performance, while a value close to 0 indicates high power consumption and poor communication performance.

[0091] As a specific embodiment, assume that the maximum power consumption of a communication module is 100 watts, and the current power consumption is 70 watts; the minimum rate of communication performance is 100 Mbps, the maximum rate is 1000 Mbps, and the current communication rate is 600 Mbps. If the weights are set , , then the comprehensive performance is calculated as follows:

[0092]

[0093] At this time, the comprehensive performance is 0.453, indicating that the communication module is in an above-average state in the trade-off between power consumption and performance.

[0094] To further improve the test efficiency, a feedback optimization mechanism is introduced. After each round of testing, the results of resource allocation are fed back, and the scheduling strategy for the next round is adjusted according to the actual test results. The feedback optimization formula is as follows:

[0095]

[0096] Among them, represents the change in the resource allocation of the i-th communication module in the next round of scheduling; the feedback process adjusts the resource allocation strategy by calculating the partial derivative of the current test result with respect to the resource allocation ratio ; the coefficient controls the speed of feedback, so that the adjustment process is neither too drastic nor too slow, ensuring the smoothness of feedback adjustment.

[0097] Through feedback optimization, the resource allocation is dynamically adjusted according to the test results of each round, so that the scheduling scheme is continuously optimized, and finally the optimal balance between power consumption testing and communication performance testing is achieved.

[0098] Embodiment 2

[0099] In an embodiment of the present disclosure, a parallel test system for the power consumption and performance of a communication module is provided, including a data acquisition module, a correlation calculation module, an impact estimation module, and a result generation module:

[0100] The data acquisition module is configured to: acquire the power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing;

[0101] The correlation calculation module is configured to: calculate the dynamic correlation between communication modules based on the multi-dimensional vector matrix of the communication module, and construct a multi-dimensional dynamic correlation matrix;

[0102] An influence estimation module, configured to: estimate the interaction influence between communication modules by using a multi-dimensional dynamic association matrix, and adjust the resource allocation ratio between communication modules according to the interaction influence;

[0103] A result generation module, configured to: after the resource allocation is completed, generate a final comprehensive test result according to the performance of power consumption and communication performance in actual tests.

[0104] Embodiment III

[0105] The purpose of this embodiment is to provide a computer-readable storage medium.

[0106] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in a method for parallel testing of power consumption and performance of a communication module as described in Embodiment I of the present disclosure are implemented.

[0107] Embodiment IV

[0108] The purpose of this embodiment is to provide an electronic device.

[0109] An electronic device, including a memory, a processor, and a program stored on the memory and executable on the processor, and when the processor executes the program, the steps in a method for parallel testing of power consumption and performance of a communication module as described in Embodiment I of the present disclosure are implemented.

[0110] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for testing power consumption and performance of a communication module in parallel, characterized in that: include: Obtain power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing; Based on the multi-dimensional vector matrix of the communication modules, the dynamic associations between the communication modules are calculated and a multi-dimensional dynamic association matrix is ​​constructed; The multi-dimensional dynamic correlation matrix is ​​used to estimate the interaction impact between communication modules, and the resource allocation ratio between communication modules is adjusted according to the interaction impact; After resource allocation is completed, the final comprehensive test results are generated based on the power consumption and communication performance in the actual test; The calculation formula of the correlation matrix is: Among them, A ij (t) represents the dynamic correlation matrix of the i-th communication module and the j-th communication module at time t; by calculating the discrete signals X i (t) and X j The time derivative of (t) to obtain their rate of change with time; The estimation formula for the interaction effect is: Among them, I ij (t) represents the interaction between the i-th communication module and the j-th communication module at time t; Through the normalization operation, the correlation degree between the i-th communication module and the j-th communication module is standardized to ensure that the sum of the interaction influence of each communication module is 1; reflects the phase difference θ between the two communication modules ij (t), and through the time variation factor Dynamically adjust the influence coefficient; parameter β is a time-dependent modulation coefficient, which is used to control the attenuation degree of the phase difference to ensure that the interaction influence is dynamically adjusted over time.

2. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 1, characterized in that: The power consumption data includes the current, voltage and power of the communication module in different working states; The communication performance data includes the signal strength, transmission rate, network delay, and signal anti-attenuation capability of the communication module; The sampling of the power consumption data and the communication performance data is performed in parallel, and the same clock source is used for synchronous sampling, so as to ensure that the power consumption data and the communication performance data at each moment can accurately correspond to the same time point.

3. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 1, characterized in that: The discretization is to eliminate the continuity in time and the data noise between different modules, construct the discrete signal of the communication module at a specific time step, and the discrete signals of all time steps in the entire test cycle to form a multi-dimensional vector matrix.

4. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 1, characterized in that: The calculation of dynamic association between communication modules is based on the multidimensional vector matrix of the communication modules, calculates the rate of change of discrete signals over time, combines the product of the rate of change with the modulation of the cosine function, obtains the influence of the phase difference between the communication modules on the dynamic association, and determines the degree of association between the communication modules.

5. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 4, characterized in that: The method of estimating the interaction between the communication modules by using the multi-dimensional dynamic association matrix quantifies the interaction between the communication modules based on the standardized association degree between the communication modules and the phase difference between the communication modules after the time variation factor is adjusted.

6. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 1, characterized in that: The resource allocation ratio between the communication modules is adjusted according to the interaction influence, and the resource allocation weight is adjusted according to the interaction influence and the feedback result by using the hierarchical scheduling model to obtain the optimal resource allocation ratio.

7. A method for testing power consumption and performance of a communication module in parallel as claimed in claim 1, characterized in that: The comprehensive test results are based on the actual power consumption of the communication module, the maximum allowable value of the power consumption, the actual communication performance, and the minimum and maximum values ​​of the communication performance. The power consumption and communication performance are evaluated in parallel, and the power consumption performance and communication performance are weighted and summed as the final comprehensive test results.

8. A communication module power consumption and performance parallel testing system, characterized in that: It includes data acquisition module, correlation calculation module, impact estimation module and result generation module: The data acquisition module is configured to: acquire power consumption data and communication performance data of the communication module, and form a multi-dimensional vector matrix through discretization processing; The association calculation module is configured to: calculate the dynamic association between the communication modules based on the multi-dimensional vector matrix of the communication modules, and construct a multi-dimensional dynamic association matrix; The impact estimation module is configured to: estimate the interaction impact between the communication modules using a multi-dimensional dynamic association matrix, and adjust the resource allocation ratio between the communication modules according to the interaction impact; The result generation module is configured to: generate a final comprehensive test result according to the performance of power consumption and communication performance in the actual test after the resource allocation is completed; The calculation formula of the correlation matrix is: Among them, A ij (t) represents the dynamic correlation matrix of the i-th communication module and the j-th communication module at time t; by calculating the discrete signals X i (t) and X j The time derivative of (t) to obtain their rate of change with time; The estimation formula for the interaction effect is: Among them, I ij (t) represents the interaction between the i-th communication module and the j-th communication module at time t; Through the normalization operation, the correlation degree between the i-th communication module and the j-th communication module is standardized to ensure that the sum of the interaction influence of each communication module is 1; reflects the phase difference θ between the two communication modules ij (t), and through the time variation factor Dynamically adjust the influence coefficient; parameter β is a time-dependent modulation coefficient, which is used to control the attenuation degree of the phase difference to ensure that the interaction influence is dynamically adjusted over time.

9. An electronic device, comprising: a memory for non-transitory storage of computer readable instructions; a processor for executing the computer-readable instructions; Wherein, when the computer-readable instructions are executed by the processor, the method according to any one of claims 1 to 7 is executed.

10. A storage medium, characterized in that: The computer-readable instructions are non-transitorily stored, wherein when the computer-readable instructions are executed by a computer, the method of any one of claims 1 to 7 is performed.

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